Genome-wide human genetic studies have identified inherited cis-regulatory loci variants that predispose to cancers. However, the mechanisms by which these germline variants influence cancer progression, particularly through gene expression and proteostasis control, remain unclear. By analyzing genomic data from a gastric cancer (GC) case-control study (2,117 individuals), focusing on the ubiquitin-specific protease (USP) family, we identify the SNP rs72856331 (G>A) in the promoter region of the proto-oncogene USP47 as a putative susceptibility allele for GC. Mechanistically, the risk allele G is associated with enhanced USP47 expression, mediated by altered recruitment of the transcription factor GLI3 and changes in the epigenetic status at promoter. CRISPR/Cas9-mediated single-nucleotide conversion into risk allele G results in increased GLI3 binding and subsequent USP47 upregulation. The depletion of GLI3 results in a reduction of cancer-related phenotypes, similar to those observed following USP47 knockdown. Furthermore, we identify Snai1 as a deubiquitination target of USP47, explaining USP47-dependent activation of the epithelial-mesenchymal transition pathway and tumor progression. Our findings identify an important genetic predisposition that implicates the perturbation of transcription and proteostasis programs in GC, offering insights into prevention and therapeutic strategies for genetically stratified patients.

Genome‐wide association studies (GWAS) have identified some single nucleotide polymorphisms (SNPs) associated with the risk of gastric cancer (GCa). However, currently, there is no published predictive model to assess the risk of GCa. In the present study, risk‐associated SNPs derived from GWAS and large meta‐analyses were selected to construct a predictive model to assess the risk of GCa. A total of 1115 GCa cases and 1172 controls from the eastern Chinese population were included. Logistic regression models were used to identify SNPs that correlated with the risk of GCa. A predictive model to assess the risk of GCa was established by receiver operating characteristic curve analysis. Multifactor dimensionality reduction (MDR) and classification and regression tree (CART) were applied to calculate the effect of high‐order gene‐environment interactions on risk of the cancer. A total of 42 SNPs were selected for further analysis. The results revealed that ASH1L rs80142782, PKLR rs3762272, PRKAA1 rs13361707, MUC1 rs4072037, PSCA rs2294008, and PLCE1 rs2274223 polymorphisms were associated with a risk of GCa. The area under curve considering both genetic factors and BMI was 3.10% higher than that of BMI alone. MDR analysis revealed that rs13361707 and rs4072307 variants and BMI had interaction effects on susceptibility to GCa, with the highest predictive accuracy (61.23%) and cross‐validation consistency (100/100). CART analysis also supported this interaction model that non‐overweight status and a six SNP panel could synergistically increase the susceptibility to GCa. The six SNP panel for predicting the risk of GCa may provide new tools for prevention of the cancer based on GWAS and large meta‐analyses derived genetic variants.

Background: Cutaneous melanoma (CM) is one of the most aggressive cancers with highly metastatic ability. To make things worse, there are limited effective therapies to treat advanced CM. Our study aimed to investigate new biomarkers for CM prognosis and establish a novel risk score system in CM.Methods: Gene expression data of CM from Gene Expression Omnibus (GEO) datasets were downloaded and analyzed to identify differentially expressed genes (DEGs). The overlapped DEGs were then verified for prognosis analysis by univariate and multivariate COX regression in The Cancer Genome Atlas (TCGA) datasets. Based on the gene signature of multiple survival associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan-Meier (K-M) analysis and log-rank test. Furthermore, the correlations between prognosis related genes expression and immune infiltrates were analyzed via Tumor Immune Estimation Resource (TIMER) site.Results: A total of 103 DEGs were obtained based on GEO cohorts, and four genes were verified in TCGA datasets. Subsequently, four genes (ADAMDEC1, GNLY, HSPA13, and TRIM29) model was developed by univariate and multivariate Cox regression analyses. The K-M plots showed that the high-risk group was associated with shortened survival than that in the low-risk group (P < 0.0001). Multivariate analysis suggested that the model was an independent prognostic factor (high-risk vs. low-risk, HR= 2.06, P < 0.001). Meanwhile, the high-risk group was prone to have larger breslow depth (P< 0.001) and ulceration (P< 0.001).Conclusions: The four-gene risk score model functions well in predicting the prognosis and treatment response in CM and will be useful for guiding therapeutic strategies for CM patients. Additional clinical trials are needed to verify our findings.

Chemotherapy resistance remains a blockade for successful treatment and longer overall survival of patients with epithelial ovarian cancer (EOC). CTNNBIP1 is an inhibitor of β-catenin that is a chemotherapeutic target for EOC treatment. In the present study, we investigated associations between single nucleotide polymorphisms (SNPs) of CTNNBIP1 and platinum treatment response of Han Chinese EOC patients and subsequently performed functional prediction and validation of the resultant SNPs. We found that CTNNBIP1 rs935072 AT/TT variant genotypes were associated with platinum treatment response in the multivariate logistic regression analysis of EOC patients. Specifically, the CTNNBIP1 rs935072 AT/TT genotypes were associated with a decreased risk of developing chemoresistance ([adjusted odds ratio (OR)] = 0.89, 95% confidence interval (CI) = 0.82-0.97 and P=0.010), compared with the AA genotype. Further experiments showed that the underlying mechanism for the CTNNBIP1 rs935072 A>T change in chemotherapy treatment response resulted from a lower binding affinity of miR-27a-3p, thereby leading to up-regulation of the CTNNBIP1 expression. We further found that overexpression of CTNNBIP1 sensitized ovarian cancer cells to platinum treatment. Thus, the present study provides evidence that functional variants of CTNNBIP1 may regulate the expression of CTNNBIP1, a possible mechanism affecting platinum treatment response of EOC patients.

Background: Although microsatellite instability (MSI) is a powerful predictive biomarker for the efficacy of immunotherapy, the mechanism of MSI in sporadic gastrointestinal cancer is not fully understood. However, epigenetics, particularly microRNAs, has been suggested as one of the main regulators that contribute to the MSI formation. Methods: We used microRNA expression data of 386 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database to identify differential microRNA expression profiles by different MSI status. We also obtained putative common target genes of the top differential microRNAs with miRanda online tools, and we analyzed these data by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment (KEGG). Results: We found that 56 and 67 gastric adenocarcinoma samples were positive for low and high MSI, respectively, and that a high MSI status was associated with age, sex and subregion (P=0.049, 0.014 and 0.007, respectively). In the 67 samples with a high MSI status, expression levels of 14 microRNAs were upregulated but five microRNAs were downregulated as assessed by the fold change (FC), compared with that of the 56 samples with a low MSI status (P2). Further analysis suggested that the expression of miR-210-3p, miR-582-3p, miR-30a-3p and miR-105-5p predicted a high MSI status (P=4.93x10(-10), 5.63x10(-1)0, 3.23x10(-9) and 7.64x10(-4), respectively). Regulation of the transcription pathways ranked the top of lists from both GO and KEGG analyses, and these microRNAs might regulate DNA damage-repair genes that were also associated with a high MSI status. Conclusions: MiR- 30a- 3p and miR- 105-5p are potential biomarkers for the MSI- H gastric adenocarcinoma, possibly by altering expression of DNA damage-repair genes.